74 citations · 131 across the 18 of their papers we have counts for
5 papers · 1 filter
Controllable Human-Object Interaction Synthesis
Jiaman Li, Alexander Clegg, Roozbeh Mottaghi +3
Synthesizing semantic-aware, long-horizon, human-object interaction is critical to simulate realistic human behaviors. In this work, we address the challenging problem of generatin…
Object Motion Guided Human Motion Synthesis
Jiaman Li, Jiajun Wu, C. Karen Liu
Modeling human behaviors in contextual environments has a wide range of applications in character animation, embodied AI, VR/AR, and robotics. In real-world scenarios, humans frequ…
Motion Question Answering via Modular Motion Programs
Mark Endo, Joy Hsu, Jiaman Li +1
In order to build artificial intelligence systems that can perceive and reason with human behavior in the real world, we must first design models that conduct complex spatio-tempor…
CIRCLE: Capture In Rich Contextual Environments
Joao Pedro Araujo, Jiaman Li, Karthik Vetrivel +5
Synthesizing 3D human motion in a contextual, ecological environment is important for simulating realistic activities people perform in the real world. However, conventional optics…
Scene Synthesis from Human Motion
Sifan Ye, Yixing Wang, Jiaman Li +4
Large-scale capture of human motion with diverse, complex scenes, while immensely useful, is often considered prohibitively costly. Meanwhile, human motion alone contains rich info…